• 기술사
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• 제44권2호
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• pp.29-33
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• 2011

In recent years, maximum electric power demand has been increasing steadily. But, Electric Power Supply & Demand problem is occurring due to lack of electric power reserve ratio caused by electric power peak. For this reason, I investigated the current status of the Electric Power Supply & Demand and established Electric Power Supply & Demand and established Electric Power Supply & Demand measures. I will expect that this paper will be contributed balanced and stable Electric Power Supply & Demand management.

• Nuclear Engineering and Technology
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• 제53권12호
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• pp.4179-4188
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• 2021

This study identifies efficient earthquake intensity measures (IMs) for seismic performances and fragility evaluations of the reactor containment building (RCB) in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). The computational model of RCB is constructed using the beam-truss model (BTM) for nonlinear analyses. A total of 90 ground motion records and 20 different IMs are employed for numerical analyses. A series of nonlinear time-history analyses are performed to monitor maximum floor displacements and accelerations of RCB. Then, probabilistic seismic demand models of RCB are developed for each IM. Statistical parameters including coefficient of determination (R²), dispersion (i.e. standard deviation), practicality, and proficiency are calculated to recognize strongly correlated IMs with the seismic performance of the NPP structure. The numerical results show that the optimal IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, A95, and sustained maximum acceleration. Moreover, weakly related IMs to the seismic performance of RCB are peak ground displacement, root-mean-square of displacement, specific energy density, root-mean-square of velocity, peak ground velocity, Housner intensity, velocity spectrum intensity, and sustained maximum velocity. Finally, a set of fragility curves of RCB are developed for optimal IMs.

• Journal of Communications and Networks
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• 제14권6호
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.301-303
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• 2000

This paper presents Kohonen neural network and wavelet transform analysis based technique for industrial peak load forecasting for the purpose of peak demand control. Firstly, one year of historical load data were sorted and clustered into several groups using Kohonen neural network and then wavelet transforms are adopted using the Biorthogonal mother wavelet in order to forecast the peak load of one hour ahead. The 5-level decomposition of the daily industrial load curve is implemented to consider the weather sensitive component of loads effectively. The wavelet coefficients associated with certain frequency and time localization is adjusted using the conventional multiple regression method and the components are reconstructed to predict the final loads through a six-scale synthesis technique.

• Advances in Energy Research
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• 제4권1호
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• pp.47-68
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• 2016

A well designed hybrid power system (HPS) can deliver electrical energy in a cost effective way. In this paper, model for HPS consisting of photo voltaic (PV) module and wind mill as renewable energy sources (RES) and solar lead acid battery as storage device connected to unidirectional grid is developed for peak demand reduction. Life time energy cost of the system is evaluated. One year hourly site condition and load pattern are taken into account for analysing the HPS. The optimal HPS is determined for least life time energy cost subject to the constraints like state of charge of the battery bank, dump load, renewable energy (RE) generation etc. Optimal solutions are also found out individually for PV module and wind mill. These three systems are compared to find out the most feasible combination. The results show that the HPS can deliver energy in an acceptable cost with reduced peak consumption from the grid. The proposed optimization algorithm is suitable for determining optimal HPS for desired location and load with least energy cost.

• 전기학회논문지
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• 제60권6호
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• pp.1225-1228
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• 2011

This paper presents an advanced energy saving algorithm in building. It is important to aggregate a various demand side resource which is controllable on demand response environment. Previous demand side algorithm for building is restricted on peak power. In this paper, we suggest duty cycle algorithm for AHU on demand response to reduce the quantity of building power consumption. The test results show that the proposed algorithm is very effective.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.68-70
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• 2003

This paper proposes the demand-side management(DSM) monitoring system of high efficient end-use appliances considering demand-side bidding (DSB). The effect on the market propagation of high efficient appliances by demand side bidding is analysed. Seasonal Peak demand forecasting and propagation capacity of these appliances are analysed.

• ETRI Journal
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• 제37권1호
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• pp.197-202
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• 2015

A smart grid is a modernized electrical grid that uses information about the behaviors of suppliers and consumers in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. In the operation of a smart grid, demand side management (DSM) plays an important role in allowing customers to make informed decisions regarding their energy consumption. In addition, it helps energy providers reduce peak load demand and reshapes the load profile. In this paper, we propose a new DSM scheduling scheme that makes use of the day-ahead pricing strategy. Based on the Rubinstein-Stahl bargaining model, our pricing strategy allows consumers to make informed decisions regarding their power consumption, while reducing the peak-to-average ratio. With a simulation study, it is demonstrated that the proposed scheme can increase the sustainability of a smart grid and reduce overall operational costs.

• 조명전기설비학회논문지
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• 제28권8호
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• pp.98-105
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• 2014

In this paper, we have analyzed the power consumption property of EVs(Electric Vehicles) chargers established in a public place, proposed reasonable demand factors by the number of established EV chargers and its control method in apartments. The optimization of power system and the suppression of the peak load can be controlled through the proposed demand factors and charging scheduling control algorithm. In this paper, electrical design and an case analysis were carried out on a sample apartment complex to prove the effectiveness of the power system. As a result, emergency power transformer capacity has been reduced by approximately 25%, and we have confirmed that the electric rates saving and the control of peak load value is possible.

• 전기학회논문지
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• 제59권9호
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• pp.1658-1662
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• 2010

This paper presents an advanced energy saving algorithm in building. It is important to aggregate a various demand side resource which is surely controllable at the peak power time to reduce the energy cost. Previous demand side algorithm appropriate for building is based on peak power. In this paper, we develop the new energy saving algorithm to reduce the quantity of power consumption. The simulation results show that the proposed tem is very effective.